Future Tech Jobs
Future Tech Jobs
Lead clinical development for vascular programmes across early and late phases, designing studies and translational plans to advance medicines for cardiovascular disease. Collaborate with cross-functional teams to shape clinical strategies, ensure patient safety, and drive innovation in drug development. Play a key role in regulatory interactions, trial oversight, and identifying transformative opportunities in vascular medicine.
Lead clinical development for vascular programmes across early and late-phase studies, shaping clinical plans and study designs to accelerate safe, meaningful medicines for vascular disease. Work cross-functionally with translational science, regulatory, safety, and commercial teams to deliver clinical development strategies and drive innovation in cardiovascular medicine.
Design and develop generative protein models that capture enzyme dynamics and function, with a focus on catalysis through motion. Analyze complex datasets and collaborate with interdisciplinary teams to evolve designs in vivo. Contribute to high-impact research publication and translation within a cutting-edge synthetic biology environment.
This role involves designing, executing, and optimizing experiments within AI-driven autonomous laboratories that integrate robotics and machine learning. The scientist will generate high-fidelity experimental data for foundation models and partner institutes, working at the intersection of laboratory science and advanced automation. The position requires a blend of scientific rigor, technical proficiency, and innovation to advance dynamic, data-rich experimentation.
This role leads clinical development for Internal Medicine assets within Pfizer's Research & Development division, serving as the primary clinical accountability point for global regulatory submissions. The individual will direct cross-functional teams in designing and executing Phase 1-3 trials, develop clinical development plans, and contribute to regulatory filings, safety reports, and product labeling. The position emphasizes leadership in obesity-related therapeutics, digital innovation in clinical development, and engagement with external scientific and regulatory stakeholders.
This role involves leading clinical development for Internal Medicine assets within Pfizer's Research & Development division, with a focus on obesity and chronic weight management. The Global Development Lead is responsible for end-to-end clinical strategy, including designing and executing global clinical trials, regulatory submissions, and cross-functional team leadership. The position requires deep therapeutic expertise, strategic input into product development, and engagement with external stakeholders such as advisory boards and regulatory bodies.
Leads end-to-end management of FSP (Functional Service Provider) resources within Clinical Operations, including workforce planning, vendor oversight, and financial control. Acts as the primary liaison between Clinical Operations and FSP vendors, ensuring resourcing strategies align with study demands and organizational frameworks. Develops data-driven forecasting models and dashboards to optimize capacity, cost, and performance across global clinical trials.
Leads the development and execution of global regulatory lifecycle strategies for assigned assets, ensuring alignment with GSK's medicine development plans and regulatory requirements across key markets. Acts as the primary regulatory point of contact on cross-functional teams, drives innovation in regulatory approaches, and provides strategic input to business development and crisis management. Directly manages a team and collaborates with senior leaders and health authorities worldwide.
Leads a team of translational genetics scientists to integrate genetic, genomic, and clinical data in support of drug discovery and development. Focuses on addressing key translational questions using statistical genetics and innovative analytical approaches across therapeutic areas such as respiratory, immunology, and neurodegeneration. Works within cross-functional teams and establishes external collaborations to advance GSK's R&D pipeline.
Leads a team of translational genetics scientists to drive data-driven insights supporting drug discovery and development across key therapeutic areas. Applies advanced statistical genetics and integrates genomics and clinical data to address translational questions. Fosters innovation, external collaborations, and scientific leadership within a multidisciplinary environment.
Leads a team of translational genetics scientists to integrate genetic, genomic (especially proteomics), and clinical data in support of drug discovery and development. Focuses on addressing key translational questions across therapeutic areas such as respiratory, hepatology, neurodegeneration, and immunology. Works within cross-functional teams and drives external scientific collaborations to advance GSK’s R&D pipeline.
Lead and execute model-informed drug development strategies in oncology, applying advanced pharmacometric and AI/ML techniques to optimize dose selection, trial design, and regulatory submissions. Work across multidisciplinary teams to drive quantitative decision-making in clinical pharmacology and contribute to the development of innovative cancer therapies.
Lead and execute model-informed drug development strategies in oncology, applying advanced pharmacometric and AI/ML techniques to optimize clinical trial design, dose selection, and regulatory submissions. Drive innovation in quantitative clinical pharmacology across the R&D pipeline, from early development through lifecycle management, within a multidisciplinary translational medicine team.
Lead the development of machine learning models to predict clinical outcomes from in silico tumor perturbations by integrating multimodal data including single-cell, spatial omics, and real-world clinical records. Collaborate with wet-lab scientists and clinicians to validate models and generate testable oncological hypotheses. Contribute to scalable, reproducible tooling and advance causal inference methods in a high-impact translational research environment.
Develop and validate machine learning models to predict clinical outcomes from in silico tumor perturbations by integrating multimodal data including single-cell, spatial omics, and real-world clinical datasets. Collaborate with wet-lab scientists and clinicians to generate testable hypotheses and inform oncology drug development decisions. Emphasis on causal inference, model interpretability, and robust software engineering practices in a translational research environment.
